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    "# 这里是判断你的目标检测算法是否运作良好。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0cbeaf1",
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    "<img src=\"./picture/交1.png\" alt=\"Drawing\" style=\"width: 500px;\" align=\"left\"/>"
   ]
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  {
   "cell_type": "markdown",
   "id": "6e75c86e",
   "metadata": {},
   "source": [
    "这里要介绍的是一个交并比来评估模型的好坏。\n",
    "\n",
    "1.这里有一个红色的框以及紫色的框，红色的是训练集本身标注的，然后紫色的是使用神经网络计算出来的。\n",
    "\n",
    "2.这两个框的交集是黄色的那个框，并集是绿色的那个框，然后$iou = $交集 / 并集，$iou$的值一般大于0.5就可以认为检测的算法效果很好，当然这个0.5是认为规定的，如果要求十分严格，也可以规定其他的数字，但是一般不会小于0.5."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "530eff58",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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